AI0-001 AI Implementation and Operations Practice Question
An ML operations team needs to monitor a deployed model's performance. Which TWO metrics are most useful for detecting concept drift in a regression model? (Choose two.)
⚠ Common exam trap
CompTIA often tests the distinction between covariate drift and concept drift, trapping candidates who think monitoring input features is sufficient for detecting all types of model degradation.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Distribution of residuals between predictions and actuals
Monitoring the distribution of residuals (predicted vs. actual values) directly reveals when the relationship between inputs and outputs has shifted, which is the essence of concept drift. In a regression model, if the residuals become systematically biased or their variance changes over time, it indicates that the underlying data-generating process has changed, even if input feature distributions remain stable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Distribution of input features
Why it's wrong here
Input feature distribution changes indicate data drift, not concept drift.
- ✓
Distribution of residuals between predictions and actuals
Why this is correct
Changing residual distribution can indicate concept drift.
- ✗
Classification accuracy
Why it's wrong here
Accuracy is for classification tasks, not regression.
- ✗
Model inference latency
Why it's wrong here
Latency is a performance metric, not related to drift.
- ✓
Mean absolute error (MAE) over a sliding time window
Why this is correct
Increasing MAE indicates model performance is degrading, suggesting concept drift.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.